f5122cdab53605b7b800c96d6700b791b8c9add8,librosa/segment.py,,lag_to_recurrence,#,287

Before Change



    sub_slice = [slice(None)] * lag.ndim
    sub_slice[1 - axis] = slice(t)
    return np.ascontiguousarray(lag[sub_slice].T).T


def timelag_filter(function, pad=True, index=0):
    """Filtering in the time-lag domain.

After Change


    if sparse:
        return rec.asformat(lag.format)
    else:
        return np.ascontiguousarray(rec.T).T


def timelag_filter(function, pad=True, index=0):
    """Filtering in the time-lag domain.
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 3

Non-data size: 5

Instances


Project Name: librosa/librosa
Commit Name: f5122cdab53605b7b800c96d6700b791b8c9add8
Time: 2016-04-26
Author: brian.mcfee@nyu.edu
File Name: librosa/segment.py
Class Name:
Method Name: lag_to_recurrence


Project Name: librosa/librosa
Commit Name: 92e6f8da63ac1d589d09c6f771d2b714aaeb5d6b
Time: 2014-05-22
Author: brm2132@columbia.edu
File Name: librosa/segment.py
Class Name:
Method Name: stack_memory


Project Name: librosa/librosa
Commit Name: 92e6f8da63ac1d589d09c6f771d2b714aaeb5d6b
Time: 2014-05-22
Author: brm2132@columbia.edu
File Name: librosa/segment.py
Class Name:
Method Name: structure_feature